Today's world is characterized by ever expanding and interconnected markets: economic, financial, social and political institutions deeply affect each other at an unprecedented rate. In this scenario market agents are exposed to “information overloading”, a phenomenon that may lead to poor investment decisions and/or missed investment opportunities. Cutting edge tools are needed to help them to discover and process relevant information.
Science of complexity brings such a tool. Complex systems are systems characterized by a huge number of elements, whose interactions are highly non-trivial and non-linear. As a result, these systems tend to exhibit peculiar behaviors that oscillate between order and randomness. Distinguishing the hidden order from the randomness is one of the main challenges of the science of complexity: once found the correct level of description, systems that seem stochastic and unpredictable can be partially controlled, monitored and predicted.
Examples of complex systems are everywhere: from biology (ant colonies, human brain) to physics (superconductors, granular materials) and social sciences (opinion dynamics, financial markets). Over the last decades the science of complexity has been one of the most interdisciplinary and promising strands of research.